package TrieTree;

/*
实现 Trie (前缀树)
Trie（发音类似 "try"）或者说 前缀树 是一种树形数据结构，用于高效地存储和检索字符串数据集中的键。这一数据结构有相当多的应用情景，例如自动补全和拼写检查。

请你实现 Trie 类：

Trie() 初始化前缀树对象。
void insert(String word) 向前缀树中插入字符串 word 。
boolean search(String word) 如果字符串 word 在前缀树中，返回 true（即，在检索之前已经插入）；否则，返回 false 。
boolean startsWith(String prefix) 如果之前已经插入的字符串 word 的前缀之一为 prefix ，返回 true ；否则，返回 false 。

作者：LeetCode
链接：https://leetcode.cn/leetbook/read/trie/x04fw7/
 */

import java.util.HashMap;
import java.util.Map;

public class _21实现Trie {
    public static void main(String[] args) {

    }

    //官解：字典树
    //数组
    class Trie {
        //一个个Tire的数组
        //被人为的划分为26个字母cell
        private Trie[] children;
        private boolean isEnd;

        public Trie() {
            children = new Trie[26];
            isEnd = false;
        }

        public void insert(String word) {
            Trie node = this;
            for (int i = 0; i < word.length(); i++) {
                char ch = word.charAt(i);
                int index = ch - 'a';
                if (node.children[index] == null) {
                    node.children[index] = new Trie();
                }
                node = node.children[index];
            }
            node.isEnd = true;
        }

        public boolean search(String word) {
            Trie node = searchPrefix(word);
            return node != null && node.isEnd;
        }

        public boolean startsWith(String prefix) {
            return searchPrefix(prefix) != null;
        }

        private Trie searchPrefix(String prefix) {
            Trie node = this;
            for (int i = 0; i < prefix.length(); i++) {
                char ch = prefix.charAt(i);
                int index = ch - 'a';
                if (node.children[index] == null) {
                    return null;
                }
                node = node.children[index];
            }
            return node;
        }
    }

    //官解 map
    class Trie2 {
        class TrieNode {
            public boolean isWord;
            public Map<Character, TrieNode> childrenMap = new HashMap<>();
        }

        private TrieNode root;

        /** Initialize your data structure here. */
        public Trie2() {
            root = new TrieNode();
        }

        /** Inserts a word into the trie. */
        public void insert(String word) {
            TrieNode cur = root;
            for(int i = 0; i < word.length(); i++){
                char c = word.charAt(i);
                if(cur.childrenMap.get(c) == null){
                    // insert a new node if the path does not exist
                    cur.childrenMap.put(c, new TrieNode());
                }
                cur = cur.childrenMap.get(c);
            }
            cur.isWord = true;
        }

        /** Returns if the word is in the trie. */
        public boolean search(String word) {
            TrieNode cur = root;
            for(int i = 0; i < word.length(); i++) {
                char c = word.charAt(i);
                if(cur.childrenMap.get(c) == null) {
                    return false;
                }
                cur = cur.childrenMap.get(c);
            }
            return cur.isWord;
        }

        /** Returns if there is any word in the trie that starts with the given prefix. */
        public boolean startsWith(String prefix) {
            TrieNode cur = root;
            for(int i = 0;i < prefix.length(); i++){
                char c = prefix.charAt(i);
                if(cur.childrenMap.get(c) == null) {
                    return false;
                }
                cur = cur.childrenMap.get(c);
            }
            return true;
        }
    }




}
